arXiv subjects

Lei Hu

Publications and source records attributed to Lei Hu.

At least 19 recordsLinked to original sources

arXiv2026

Enhancing Table Structure Recognition via Bounding Box Guidance

Table Structure Recognition (TSR) aims to extract the bounding boxes of cells and table structure (e.g., HTML) from table images. Although current approaches have made significant progress, the latest image-to-sequence methods overlook the explicit utilization of the bounding box information when predicting HTML sequences, leading to error predictions in complex scenes. In this paper, we introduce a novel framework BGTR (Bounding Box-Guided Table Recognizer). To more effectively utilize bounding box information, we first predict the bounding boxes of cells and then use this information to guide the generation of HTML sequences. While utilizing bounding box information can enhance the accuracy of HTML sequences, for natural scene tables, the data volume is too small to allow for sufficient training of bbox-guided HTML generation. In response, we adopt a progressive training method for natural scene tables and introduce SNSTab, a synthetically generated natural scene table dataset. Our experiments on five benchmark datasets demonstrate SOTA performance.

cs.CV↗

arXiv2026

NEXUS: Transient Searches and First Results from Year One Observations

We describe ongoing efforts of high-redshift transient searches using multi-epoch NIRCam imaging (F200W+F444W) and NIRSpec MSA/PRISM spectroscopy from the NEXUS JWST multi-cycle Treasury program targeting the north ecliptic pole region. The transient search area covers $\sim 61.5\,{\rm arcmin^2}$ between the reference epoch and each subsequent NEXUS-Deep epoch at a cadence of $\sim2$~months. In the first year of observations from NEXUS, we detect 68 robust transients, with the host photometric redshift distribution declining rapidly at $z>2$ but extending to $z_{\rm phot}\approx 6$. In addition, we obtained secure spectroscopic redshifts for 37 transients ($\sim54\%$) from NIRSpec/PRISM and NIRCam/WFSS, with seventeen at $1 < z < 2$, eight at $2 < z < 3$, two at $3 < z < 4$, and one tentative host association at z = 6.151. Overall, the NEXUS program recovers observed supernova (SN) rates broadly consistent with other SN search programs with JWST. While NEXUS achieves the highest transient detection efficiency, 6.6 SNe per imaging hr ($2.6\times$ COSMOS-SN and $26\times$ JADES-SN), the limited filter coverage (F200W+F444W only) limits robust identification and classification of high-$z$ SNe for deep spectroscopic follow-up. We describe the details of the data reduction and transient detection pipeline, and report the Year-1 transient sample along with their light curves, available MSA spectroscopy, host association, and the raw detection rate. We also describe and release a new PSF photometry package that properly accounts for correlated pixel noise from combining drizzled images.

astro-ph.HE↗

arXiv2026

Advancing All-Weather Building Damage Mapping to the Instance Level: Outcomes and Insights from the 2026 Bright Challenge

Rapid post-disaster response requires timely, building-level information on whether structures remain intact, are damaged, or are destroyed. Post-event optical imagery, however, may be unavailable because of cloud, smoke, or darkness. The Bright Challenge evaluated all-weather building damage mapping from a submeter-resolution pre-event optical image and a post-event SAR image. Participants were required to detect and delineate each building and assign exactly one of three mutually exclusive damage labels. The challenge extended the globally distributed \textsc{Bright} dataset with instance-level annotations for about 291,000 buildings across 16 disaster events spanning seven disaster types. The final phase was evaluated exclusively on two 2025 events absent from training: a wildfire event in California and a hurricane in Jamaica. A total of 157 participants made 1,289 submissions, and 46 teams entered the final phase. The two winning solutions achieved test mAPs of 0.182 and 0.181, approximately 8.7 times the public baseline of 0.021, but remained far below the best in-domain holdout score of 0.513. Across teams ranked in both phases, performance declined sharply and the rank order changed substantially. The two leading solutions independently favored modality-specific encoding, staged or late optical--SAR fusion, and an optical-dominant separation of building localization from damage recognition. The winning method additionally used scene-aware threshold adjustment and pseudo-label adaptation. These results identify cross-event generalization and stable severity discrimination as the principal remaining challenges. All data, annotations, baseline code, and winning solutions are publicly available at https://github.com/ChenHongruixuan/BRIGHT.

cs.CV↗

arXiv2026

IMMoE: Incomplete Multi-View Anomaly Detection via Mixture of View Experts Fusion

Existing Multi-view Anomaly Detection (MAD) methods assume that all views are completely available and model each view separately. However, in real industrial scenarios, information in the view may be missing due to faults such as occlusion, which leads to the performance degradation of existing methods due to the lack of a multi-view consistency prior. To address this, we explored a more challenging task: Incomplete Multi-View Anomaly Detection (IMVAD), in which some areas of each view were masked. We proposed a pipeline for automatically generating the IMVAD dataset and generated the \textbf{RIMAD} dataset based on the Real-IAD dataset through this pipeline. In addition, in order to effectively utilize the information of multiple views in the absence of view information, we propose \textbf{IMMoE}, which consists of two key modules: (1) Multi-View Expert Fusion (MVEF) effectively fuses multi-view information through a multi-view expert network and guides the reconstruction of a single view; (2) Local Anomaly Enhancement Encoder (LAEE) effectively prevents the model from overfitting the mask region by applying dropout to local features. Our method achieves state-of-the-art performance on both the RIMAD and Real-IAD datasets, especially on RIMAD, we have increased the pixel-level and image-level metrics by 11.8\% and 2.8\%, respectively. Our source code is available at https://github.com/HULEI7/IMMoE

cs.CV↗

arXiv2026

First Results from the LSST Shadow Survey: The Restless Luminous Blue Variable AT2017des in the Virgo-Cluster Galaxy, NGC4532

The Legacy Survey of Space and Time (LSST) will start in late-summer 2026, revolutionizing transient astronomy. Here, we present the Dark Energy Camera (DECam) Shadow Survey, which is designed to maximize the science potential of LSST by shadowing LSST observations of local galaxy-cluster fields, producing a nightly cadence of these fields. The Shadow Survey will discover extremely young supernovae (SNe), SN precursors, as well as other explosive transients and exotic phenomena, helping to characterize such transients at unprecedented cadence and depth when combined with LSST. We describe our workflow, pipeline, public data releases, and candidate vetting. As an early result of Shadow, we present the fitful luminous blue variable (LBV) eruptions of AT2017des in the Virgo-Cluster galaxy NGC4532. AT2017des has short-timescale variability (of order 10 days), peaking at around $M_r=-12.5$mag, brighter than normal LBVs, and similar to the more extreme flaring of hot LBVs/SN impostors such as SN2000ch, AT2016blu, and the precursor activity of SN2009ip. Our spectral time-series reveals features typical of these hot LBVs and SN impostors/precursors. Combining our data with long-baseline photometry from additional observatories, we find that the peaks of the outbursts of AT2017des are getting brighter over time, with 2026 peak fluxes being up to 5 times greater than in 2023 and an average brightening of $\sim0.05$ mag yr$^{-1}$. The peaks of AT2017des are more luminous than those of most other LBVs, only being fainter than bright precursors such as SN2009ip, and extreme SN impostors such as AT2016blu. AT2017des may therefore be ``ramping up'' to a terminal explosion.

astro-ph.HE↗

arXiv2026

Discovery of a Supernova Following the Einstein Probe Transient EP250302a at z = 1.131

We present a multi-wavelength analysis of the Einstein Probe (EP) fast X-ray transient (FXT) EP250302a located at redshift $z=1.131$. Despite its luminous prompt X-ray emission, the event was not detected in gamma-rays. Multi-wavelength follow-up identified a bright optical and X-ray source that displayed rapid chromatic flaring before returning to the standard decay of a gamma-ray burst afterglow. We interpret the chromatic flare as either due to a refreshed shock caused by a discrete shell collision or as reverse shock emission. Using the early optical data, we place constraints on the Lorentz factor of the outflow, requiring an ultrarelativistic jet with $\Gamma_0>25$. We additionally obtained deep late-time imaging with the Gemini North Telescope that reveals the presence of an optical excess at $20-30$ d post-explosion. We interpret this as supernova (SN) emission and find good agreement with the canonical broad-lined Ic SN 1998bw with a flux-scaling factor of $k_\textrm{98bw}>0.3$. This adds to the growing evidence that the majority of EP FXTs are associated with the deaths of massive stars.

astro-ph.HE↗

arXiv2026

GUITrans2Act: Understanding User Operational Behaviors from Mobile GUI Interactions with Vision-Language Models

Understanding the digital world on mobile devices is shifting from static UI perception to dynamic action comprehension. This capability enables models to convert visual state transitions into operational knowledge, defined as short natural-language sentences that describe action types, target UI elements, textual arguments, and execution orders. However, due to the highly diverse and heterogeneous UI designs across applications, existing vision-language models (VLMs) struggle to accurately infer these underlying operations. To bridge this gap, we introduce Teach VLM, a core model designed to translate mobile screen trajectories into step-wise operational knowledge by extracting and analyzing operation-related keyframes from demonstration videos. To address the scarcity of aligned training data, we develop a systematic data flywheel for scalable data acquisition. We further introduce a novel Chinese Mobile Screen Teach Benchmark for fine-grained evaluation. Building upon Teach VLM, we propose the Teach-and-Repeat paradigm, where the generated operational knowledge serves as an interpretable procedural reference to guide downstream screen-based execution agents. Extensive evaluations demonstrate that Teach VLM significantly outperforms strong VLM baselines, achieving state-of-the-art performance in operation semantics prediction. Furthermore, experiments in Android World show that our paradigm yields consistent Task Success Rate improvements for downstream agents. Together, Teach VLM and the Teach-and-Repeat paradigm offer a practical pathway from raw demonstrations to reusable task automation.

cs.AI↗

arXiv2026

EP260321a/SN 2026gzf: The Faintest Shock Breakout Associated with a Broad-Lined Supernova

The explosion of a star is first marked by the shock wave breaking out of the stellar surface, producing a burst of ultraviolet and X-ray radiation. These events are observationally rare, despite likely accompanying the majority of supernovae. Here, we report on our multi-wavelength observing campaign of the closest Einstein Probe fast X-ray transient EP260321a at $z=0.0344$. The thermal ($kT=130$ eV) X-ray emission with peak luminosity $1.0\times10^{45}$ erg s$^{-1}$ points to a shock breakout origin. We demonstrate that EP260321a is accompanied by a broad-lined Type Ic supernova, SN 2026gzf. The supernova properties, including its spectral evolution, lightcurve evolution, and expansion velocities, are all typical of the energetic stripped-envelope supernovae associated with gamma-ray bursts. However, deep X-ray upper limits obtained with the \textit{Chandra X-ray Observatory} do not detect an X-ray afterglow, and instead exclude the afterglow of known gamma-ray bursts or fast X-ray transients. If the stellar explosion launched a successful relativistic jet, we require that it had both a low Lorentz factor $\Gamma_0$\,$<$\,$30$ and a kinetic energy $E_\textrm{kin}$\,$<$\,$10^{49}$ erg for a stellar wind density of $A_*$\,$\gtrsim$\,$1$. We propose that EP260321a originated from a mildly relativistic, weak outflow that was choked by the progenitor star. This scenario is capable of naturally explaining its low X-ray luminosity and lack of prompt gamma-ray emission. EP260321a bridges the gap between SN 2008D and low-luminosity GRBs, suggesting a greater diversity in the physical parameters of stripped stars as they undergo terminal collapse.

astro-ph.HE↗

arXiv2026

Simultaneously Minimizing Storage and Bandwidth Under Exact Repair With Quantum Entanglement

We study exact-regenerating codes for entanglement-assisted distributed storage systems. Consider an $(n,k,d,\alpha,\beta_{\mathsf{q}},B)$ distributed system that stores a file of $B$ classical symbols across $n$ nodes with each node storing $\alpha$ symbols. A data collector can recover the file by accessing any $k$ nodes. When a node fails, any $d$ surviving nodes share an entangled state, and each of them transmits a quantum system of $\beta_{\mathsf{q}}$ qudits to a newcomer. The newcomer then performs a measurement on the received quantum systems to generate its storage. Recent work [1] showed that, under functional repair where the regenerated content may differ from that of the failed node, there exists a unique optimal regenerating point that \emph{simultaneously minimizes both storage $\alpha$ and repair bandwidth $d \beta_{\mathsf{q}}$} when $d \geq 2k-2$. In this paper, we show that, under \emph{exact repair}, where the newcomer reproduces exactly the same content as the failed node, this optimal point remains achievable. Our construction builds on the classical product-matrix framework and the Calderbank-Shor-Steane (CSS)-based stabilizer formalism.

cs.IT↗

arXiv2026

Electromagnetic Follow-up of the Sub-Solar Mass Gravitational Wave Candidate S251112cm: Kilonova Constraints and a Coincident IIb Supernova

On November 12th, 2025 the LIGO--Virgo--KAGRA (LVK) collaboration reported gravitational waves (GWs) from a compact object merger candidate (S251112cm) with at least one sub-solar mass component. Using the Dark Energy Camera (DECam), the Fraunhofer Telescope at Wendelstein Observatory (FTW), and the Zwicky Transient Facility (ZTF), we surveyed $56\%$ of the GW localization region beginning $2.4$~hours after the GW alert. We find no kilonova (KN) counterpart, and use radiative-transfer models to rule out $42\%$ (ZTF), $68\%$ (DECam), and $92\%$ (FTW) of the KN models as possible emission from this GW candidate. Within the recently proposed disk-fragmentation (``superkilonova'') model for generating sub-solar mass neutron star mergers from stellar core-collapse, the delay between the supernova explosion time and the GW merger time is estimated to be less than a few days. Searching this time window prior to the GW event, we identify and spectroscopically classify a IIb supernova (SN~2025adtq), with a spatial association odds ratio of $\log_{10}\mathcal{I} \approx 4.8$, a chance coincidence probability of ${\sim}2$--$9\%$, and an estimated explosion time ${\sim}2$ days prior to S251112cm. SN~2025adtq is the second Type~IIb supernova found in spatial and temporal coincidence with a sub-solar mass GW candidate, following the previously reported S250818k/SN~2025ulz association; jointly, we measure an odds ratio that favors the association hypothesis over the null, however, when conditioned on finding a coincident supernova by chance, the odds ratio disfavors association. Together, these results provide suggestive but inconclusive evidence for the superkilonova formation channel.

astro-ph.HE↗

arXiv2026

SN 2025adpq: A Type Ia supernova in a collisional ring formed during a major galaxy merger

Galaxy mergers can both trigger star formation and rearrange where stars live, producing long-lived tidal structures and collisionally driven density waves (known as collisional rings) that can extend for tens of kpc from their host galaxy centers. Here we report the discovery of SN 2025adpq, a Type Ia supernova at $z=0.1540$, found within a collisional ring, which we call Pika's Halo, with circumference $\sim$\,70 kpc that was produced by a major merger between two comparable mass galaxies ($\log(M_*/M_\odot)\approx10.5)$. The supernova lies along the ring at a projected offset of $\sim$11.4 kpc from the nucleus of the primary galaxy (hereafter G1). Optical spectroscopy obtained with the Southern African Large Telescope (SALT) and Gemini South reveal signatures consistent with merger induced ongoing star formation, while prominent Calcium H and K absorption indicates a substantial old stellar population within the ring. Therefore, we propose that SN 2025adpq may have been produced by an old progenitor system that was displaced from G1 during the head-on encounter. In this scenario, the progenitor was stripped from its parent galaxy by the collisionally induced pressure wave and exploded far from its birthplace. However, given the broad diversity in SN Ia delay times, we cannot conclusively demonstrate that the progenitor was not formed in a more recent burst of star formation triggered by the expanding pressure wave. Regardless, SN 2025adpq highlights collisional rings as a path to large offset SNe Ia, and it motivates targeted searches for faint, dynamically displaced old populations in seemingly hostless environments. We additionally identify other supernovae, including supernova siblings, in the low redshift sample of collisional ring galaxies, and find that SN 2025adpq is one of only a handful of classified supernova identified in the expanding ring of a collisional ring complex.

astro-ph.GA↗

arXiv2026

A GPU-Accelerated Transient Detection Pipeline for DECam Time-Domain Surveys

We present a GPU-accelerated transient detection pipeline developed for time-domain surveys with the Dark Energy Camera (DECam). It enables real-time-capable image processing, incorporating science-driven candidate filtering to support rapid transient identification in time-critical observing programs. The pipeline serves as the core transient discovery engine for multiple long-term DECam programs, including the GW-MMADS gravitational-wave follow-up campaign and the DESIRT survey for intermediate-redshift transients with DESI synergy. The pipeline ingests calibrated imaging products from the DECam Community Pipeline and performs image differencing using the SFFT algorithm, coupled with CNN-based real-bogus classification, to produce science-ready transient alerts and light curves that are delivered to community brokers. We validate the pipeline using archival DECam data from the DESIRT survey. The real-bogus classifier achieves a completeness of $\sim$ 99\% of real transients while rejecting $\sim$ 96\% of subtraction artifacts, and the workflow typically reduces the candidate load to a manageable level for survey operations. With GPU acceleration, the typical processing time per DECam exposure is $\sim$ 50 s from calibrated image processing to alert generation using a modest allocation of computing resources.

astro-ph.IM↗

arXiv2026

NEXUS: Quick Release Notes

NEXUS is a JWST Multi-Cycle (Cycles 3-5) GO Treasury imaging and spectroscopic survey around the North Ecliptic Pole during 2024-2028. It contains two overlapping tiers in depth and area coverage. The Wide tier ($\sim 400~{\rm arcmin}^2$) performs NIRCam/WFSS 2.4-5 $\mu$m grism spectroscopy with three annual epochs over 3 years (final spectral continuum ${\rm S/N/pixel>3}$ at F444W $<22.2$), accompanied by NIRCam multi-band imaging in F090W, F115W, F150W, F200W, F356W and F444W. The Deep tier ($\sim 50~{\rm arcmin}^2$) performs high-multiplexing NIRSpec 0.54-5.5 $\mu$m MOS/PRISM spectroscopy for ~10,000 targets in total, over 18 epochs with a 2-month cadence, along with F200W+F444W NIRCam imaging for each epoch. Parallel imaging observations with MIRI and additional NIRCam filters are also performed within the Wide and Deep tiers. The primary data covering the Deep tier (including NIRCam imaging, NIRSpec/MSA spectra, and vetted MSA spectroscopic redshifts) are released in regular Quick Data Releases to facilitate follow-up studies. This evolving document describes the MSA targeting information and observing status for each of the 18 Deep epochs, which started in May 2025 and continue on the regular 2-month cadence. We also describe the content and caveats of the quick release data and report selected cases of diverse scientific interests.

astro-ph.IM↗

arXiv2026

The environmental dependence of mid-IR luminous dusty Supernovae

Using the Spitzer and WISE images, we discovered 42 mid-IR luminous dusty supernovae with local integral-field spectroscopy data. The observed mid-IR emission indicates the presence of newly formed dust, or pre-existing dust heated by the radiation from the supernovae or circumstellar medium interactions. We carried out a systematic analysis of the supernova host environments and their dust properties, for understanding the dust-veiled exploding stars, and whether such an intense dust production process is associated with their local environments. We find that dusty supernovae prefer the locations with higher EW(H{\alpha}), lower metallicity, and heavier host extinctions compared to typical SN types, and they show the same increasing sequence in the values of EW(H{\alpha}) and oxygen abundance from hydrogen-rich, type IIn and hydrogen-poor dusty supernovae. These differences in environmental properties of different dusty SN types indicate the diversity of their progenitors. We also found that one marginal correlation is a negative correlation between the SN dust mass and star formation rate. This means that SNe would be more mid-IR luminous and more dust-rich at the region with lower star formation rate. However, the SN dust mass show no correlation with the metallicity and the host extinction, which were thought to be key factors affecting the mass-loss history of progenitors and the CSM environment of SNe. Therefore, the dust formation process in SNe might be insensitive to metallicity and the dust condition of their host environments.

astro-ph.HE↗

arXiv2026

WFST Supernovae in the First Year: I. Statistical Study of 16 Early-phase Type Ia Supernovae from the Pilot Survey

In this paper we present 16 early-phase type Ia supernovae (SNe Ia) discovered during the pilot survey of the 2.5-meter Wide Field Survey Telescope (WFST-PS) from March 4 to July 10, 2024, including three SNe Ia with early-excess emission features (EExSNe Ia). The discovery magnitude of the 16 WFST-PS early-phase SNe is at least 3 mag fainter than their peak brightness. A large scatter of color indices is found in approximately the first 10 days of supernova explosions, indicating diverse photometric behaviors in the early phase. Three EExSNe Ia show relatively brighter peak luminosities and longer rise time compared to those of non-EExSNe Ia. The results indicate that current theoretical models require further refinement to fully capture the early photometric evolution of SNe Ia. Based on the initial high-cadence ugr-band data from the WFST-PS survey, we emphasize that early near-ultraviolet (NUV) observations are indispensable for placing tight constraints on the explosion mechanisms and progenitor systems of SNe Ia.

astro-ph.HE↗

arXiv2026

WFST Supernovae in the First Year: II. SN 2024aedt: Systematical Study of a Transitional Type Ia Supernova

We present comprehensive photometric and spectroscopic observations of a transitional type Ia SN 2024aedt, discovered by the 2.5-meter Wide Field Survey Telescope (WFST) within one day of the explosion. Its light curve is characterized by a peak absolute magnitude of $M_B = -18.49 \pm 0.03$ mag and a decline rate of $\Delta m_{15}(B) = 1.53 \pm 0.36$ mag, placing the object on the $\Delta m_{15}(B)$--$M_B$ diagram in the transition region between normal and subluminous SNe Ia. Furthermore, the early-color evolution and host galaxy environment of SN 2024aedt underscore its transitional nature, sharing properties with both normal and 91bg-like SNe Ia. Light-curve modeling with MOSFiT yields a synthesized $^{56}\mathrm{Ni}$ mass of $0.414 \pm 0.042\,M_{\odot}$ and a total ejecta mass of $0.548 \pm 0.108\,M_{\odot}$. A comparison with theoretical models suggests that the evolutionary trend can be broadly explained by both delayed-detonation (DDT) and double-detonation (DDet) scenarios while possible early-excess emissions predicted by DDet cannot be identified given the limited detections soon after the SN explosion. Although the overall spectral evolution of SN 2024aedt is similar to that of other transitional SNe Ia, the spectroscopic comparison reveals diversity in the early-phase blue-end features, which becomes more homogeneous at later phases. The result indicates the importance of early-time observations in understanding the origin of SN Ia diversity.

astro-ph.HE↗

arXiv2026

Illuminating the Mass Gap Through Deep Optical Constraint on a Neutron Star Merger Candidate S250206dm

The gravitational wave (GW) event S250206dm, as the first well-localized neutron star merger candidate potentially located in the mass gap, presented a unique opportunity to probe the electromagnetic signatures from such a system. Here we report a deep, multiband search with the new 2.5-meter Wide Field Survey Telescope (WFST), covering about 64% of the localization region up to a 5-sigma limiting magnitude of 23 mag. In total, 12 potential candidates have been identified while none of them are likely related to S250206dm. This non-detection provides the most stringent constraint to date on any associated kilonova. Crucially, an AT 2017gfo-like event at 269 Mpc can be excluded by WFST observations alone. Based on ejecta mass limits, a neutron star-black hole with a large mass ratio (Q >= 3.2) is disfavored. This optical-derived constraint on the mass ratio reaches, for the first time, a precision comparable to that inferred from the GW signal. This work presents the best observation of this type of events until now, and demonstrates the power of rapid, deep follow-up observations to constrain the properties of compact binary progenitors, offering key insights into the constituents of the mass gap.

astro-ph.HE↗

arXiv2026

STProtein: predicting spatial protein expression from multi-omics data

The integration of spatial multi-omics data from single tissues is crucial for advancing biological research. However, a significant data imbalance impedes progress: while spatial transcriptomics data is relatively abundant, spatial proteomics data remains scarce due to technical limitations and high costs. To overcome this challenge we propose STProtein, a novel framework leveraging graph neural networks with multi-task learning strategy. STProtein is designed to accurately predict unknown spatial protein expression using more accessible spatial multi-omics data, such as spatial transcriptomics. We believe that STProtein can effectively addresses the scarcity of spatial proteomics, accelerating the integration of spatial multi-omics and potentially catalyzing transformative breakthroughs in life sciences. This tool enables scientists to accelerate discovery by identifying complex and previously hidden spatial patterns of proteins within tissues, uncovering novel relationships between different marker genes, and exploring the biological "Dark Matter".

cs.AI↗